Bibliographic record
Abstract
A solicitud de la dirección de La Otra Economía, acepté con prontitud escribir en cada número de la revista una crónica sobre la economía social y solidaria (ESS) en América del Norte. Para mi primera crónica, me vino la idea de compartir algunas reflexiones sobre los retos del “mapeo” de la ESS tomando algunas enseñanzas de las experiencias de mapping que hemos conocido estos últimos años en Quebec y en Canadá dentro de nuestros equipos de investigación en partenariat sobre la ESS. Para tal efecto, tengo la intención de hacer tres cosas en el texto siguiente. En principio, recordar el contexto en el cual la cuestión del mapping despierta mi curiosidad. Luego, explicar porqué una reciente contribución latinoamericana puede constituir un punto de referencia estimulante para nuestra reflexión crítica sobre el mapping en Canadá. Finalmente, presentar un balance y las enseñanzas de experimentaciones que nosotros hemos tenido en Quebec y Canadá concernientes al mapping en el curso de la última década.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.008 | 0.019 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".